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Nick Foles Will Be the Starting Quarterback

| June 1st, 2020


For the Bears, there is no more important issue looming than which man will be under center receive the shotgun snap when the Bears take the field against Detroit in Week One. Today I want to dig into the stats to see what we can learn about Foles vs. Trubisky, as well as what to expect from whoever wins that derby compared to other QBs around the NFL.

The table below shows basic efficiency statistics for Trubisky and Foles in the Reid offense (so Trubisky in 2018-19 in Chicago and Foles in 2016 in KC and 17-18 in Philadelphia), plus the other three notable recent Reid QBs (Smith 13-17, Mahomes 18-19, Wentz 16-19). I’ll note I included playoff stats for everybody because otherwise Foles’ sample size is just so small (less than 350 with just regular season, just over 500 with playoffs included). I also included the NFL average for 2018-19 as a frame of reference for what’s roughly normal around the league. I split up the data into short and long passes (targeted more than 15 yards past the line of scrimmage) using Pro Football Reference’s game play finder.

That’s a lot of information to digest, so let’s look at short and deep passes separately.


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What are the Bears Getting in Nick Foles?

| March 19th, 2020

The Bears traded a 4th round pick for Nick Foles, and the Bears officially have their new quarterback.

On the surface it might seem puzzling to trade for a 31 year-old quarterback who hasn’t thrown 200 passes in a season since 2015, but one of the big draws for Foles was his familiarity in Matt Nagy’s offense. He played for Nagy in Kansas City in 2016 and in the same scheme in Philadelphia under Doug Pederson in 2017-18. This could be especially important in this offseason, when team activities might not happen before training camp due to Covid-19.

Let’s take a look at some advanced statistics to see how Foles has performed in this offense. In my view, advanced statistics tell us as much about a quarterback’s approach as they do his efficiency. From them, you can see if he favors holding the ball to make a play or getting it out quickly to avoid taking a sack, pushing it deep or throwing it underneath, and making safe passes or taking chances into coverage.

The table below shows a battery of advanced statistics for Foles from 2016-18. For comparison, I included Mitchell Trubisky’s stats from his time under Nagy, and also Alex Smith’s from his time in this offense in Kansas City (the Next Gen Stats database only goes back to 2016, so I couldn’t make his sample any larger). I’ll note that Foles’ stats include playoff games to make the sample a bit bigger; even with that, it’s barely over 500 passes, and about 1/3 of that comes from the playoffs. I color-coordinated columns into general categories: basic efficienty stats (gray), throwing distance (blue), throwing time (tan), and taking chances (green). All data comes from Next Gen Stats except deep passes, which are from Pro Football Reference.

A few thoughts:

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The Non-Trubisky Offensive Issue: Personnel Usage Remains a Problem

| February 10th, 2020

It’s no secret that I’ve blamed quarterback Mitchell Trubisky for the lion’s share of Chicago’s offensive shortcomings in 2019, while pointing out contributing factors elsewhere: tight end, run blocking, Tarik Cohen…etc. But I truly believe that a competent quarterback would have put the Bears in the playoffs in 2019.

However, it’s important not to get too fixated on one issue and ignore other problems. So today I want to look at offensive issues from 2019 that have absolutely nothing to do with Mitchell Trubisky, but instead are due to what I believe to be poor coaching decisions regarding personnel usage.


Personnel Predictability

How predictable was Chicago’s offense when several of their key players were on or off the field?

The table below shows changes in run percentage when skill position guys who played between 35-65% of the snaps were in the game vs. on the sideline.

  • On the high end, that excludes players who almost never leave the field (Allen Robinson played over 93% of offensive snaps in 2019) because their “off field” splits would be too small to be worth considering.
  • On the low end, it excludes situational players who often only come in for situations where a run or pass is expected (ie the 4th WR in a 4 WR set for 3rd and long, or the 2nd TE in a short-yardage set).

Instead, I want to look at how the Bears deployed their key skill position players as they rotated through in a game.

(Note: This data is pulled from the NFL Game Statistics and Information System, which includes sacks and QB scrambles as passing plays.)

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Least Explosive Team in the NFL, or the Story of the 2019 betway平台

| February 4th, 2020

I’ve been working my way through the Bears’ 2019 performance to see what changed from 2018 that caused them to slip from 12-4 to 8-8. Today, I want to look at explosive plays, which I found last season have a strong correlation to overall offensive performance.

There are a variety of definitions for explosive plays depending on who you ask, so I want to clarify I’m using parameters laid out by ESPN NFL Matchup, which counts any run that gains 15+ yards or pass that gains 20+ yards as explosive. Let’s start with a preliminary look at how the Bears did in 2019 relative to the rest of the NFL. All data is from Pro Football Reference, with explosive play information coming from the Game Play Finder. Pass percentages were calculated including sacks and pass attempts as pass plays.



That’s ugly.

If you want to compare to 2018, the Bears slipped across the board. They had 71 explosive plays in 2018, with explosive rates of 7% overall, 5.3% on runs, and 8.4% on passes. All of those numbers in 2018 were slightly below average, ranging from 18th to 21st in the league, while they are all bottom 2 in 2019.

So what happened to cause such a slump? Like I’ve done when evaluating both the running and passing games, I want to break down what it looks like for individual Bears players and/or position groups from season to season. That information is shown in the table below, with all cells formatted by 2018 / 2019 data. (I’ll note the pass rates are a bit higher for pass catchers than QBs because they are only out of targets and exclude sacks and throwaways.)


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What Changed in the Passing Game: Volume III

| January 24th, 2020

Today I want to look back at two areas of concern I noted for Trubisky last off-season: deep passes and performance against good defenses.


Deep Passes

Last year, I noted that Trubisky was really good at short passes (15 yards or less past the line of scrimmage) and really bad throwing the ball deep. I also found that appbetway必威亚洲官网 , which gave us a reason to be optimistic about Trubisky heading into 2019.

Let’s see how that theory played out in 2019.

A few thoughts:

  • So much for short stuff being consistent. Trubisky’s completion percentage, yards/attempt, yards/completion, and touchdown rate all plummeted from 2018 to 2019.
  • Some of the completion percentage can be accounted for by drops (as I have previously addressed), but not nearly all of it on the short stuff. Despite throwing shorter passes in the short stuff, Trubisky completed fewer of them. The end result was an extremely inefficient short passing game.

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What Changed in the Passing Game: Volume II

| January 23rd, 2020

Yesterday, it was discovered that the pass blocking and drops by pass catchers went from really good to about average.

The hypothesis, then, is that the quarterback was largely responsible for the Bears having one of the worst passing games – and thus worst offenses – in the NFL. So today I want to look at Mitchell Trubisky’s performance more closely to see what it can tell us.

On the surface, Trubisky certainly was awful in 2019. He completed 63.2% of his passes (18th in the NFL), averaged 6.1 yards/attempt (last), and posted a passer rating of 83.0 (28th). This was a big step back from 2019, when he was near average in all of those marks (66.6% completion, 14th; 7.4 yards/attempt, 18th; 95.4 rating, 16th).

Evaluating a quarterback’s play statistically can be tricky, because his stats depend both on his offensive line’s ability to block for him and his RBs/WRs/TEs’ ability to catch his passes, both of which are outside of his control. That’s why I started by looking at the offensive line and drops, both of which were worse in 2019 than 2018 but not nearly bad enough to explain bottom 5 production from the quarterback.

It’s also worth noting that Chase Daniel’s production barely changed between seasons. In 2018, he completed 70% of his passes, averaged 6.8 yards/attempt, threw 3 TD and 2 INT, and posted a 90.6 passer rating. In 2019, he completed 70% of his passes, averaged 6.8 yards/attempt, threw 3 TD and 2 INT, and posted a 91.6 passer rating. To be fair, it’s a small sample size – he played 2 games and threw around 70 passes each year – but still, this is at least anecdotal evidence to support the notion that the offense as a whole didn’t change all that drastically.


Advanced Stats

With that said, let’s look more closely at Trubisky’s performance to see if we can hone in on what changed, besides worse pocket presence and less running impact, which were touched on in previous articles. This is going to focus on passing. We’ll start by looking at a smattering of advanced statistics, which come from a combination of Next Gen Stats and Pro Football Reference.

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What Changed in the Passing Game: Volume I

| January 22nd, 2020

It stands to reason that if the offense was mainly responsible for the Bears’ 2019 regression, and the running game didn’t change all that much, most of the regression came from the passing game. And a quick look at the stats backs that up. In 2018, the Bears were 9th in completion percentage, 18th in yards/attempt, 14th in passer rating, and 10th in sack percentage. In 2019, those ranks fell to 14th, 32nd, 24th, and 23rd.

So what went wrong in the passing game? Generally, there are 3 components to examine: the pass protection, the pass catchers, and the quarterback. Let’s look at each one by one.


Pass Protection

Evaluating pass protection statistically is difficult, but thankfully advanced statistics to help with this are getting better. A number of them are shown below, with their ranks out of 32 NFL teams in parentheses. Average time to throw is from Next Gen Stats, Average time to pressure and pressure rate is from Pro Football Reference, and Pass Block Win Rate – a measure of how often a QB has a clean pocket for at least 2.5 seconds, is from ESPN Metrics (source for 2018 and 2019).

 

As I tried to make sense of these numbers, it seemed to me that the change in NFL ranks was often greater than the change in the actual value. Sure enough, it seems that pass blocking was slightly better across the league in 2019 than 2018. The median average time to pressure increased from 2.4 to 2.5 seconds, the median pressure rate dropped from 24.1% to 22.6%, and the median pass block win rate increased from 50% to 59%.

Looking just at the Bears’ numbers, they generally got a little worse in pass protection, but their drop in the rankings looks worse than it is because the rest of the NFL got better. The average time to throw didn’t change all that much and the pressure got there a little faster, but the Bears still ranked right around average both in pressure rate and pass block win rate.

If the pass protection didn’t get much worse, how do we account for the massive uptick in sacks? The Bears went from giving up 33 sacks in 2018 (6.1% of dropbacks) to 45 in 2018 (7.2% of dropbacks).

Well, sacks aren’t only due to the pass blocking, they’re a result of the quarterback as well. Lester Wiltfong of Windy City Gridiron breaks down film on every sack and assigns blame to the person or people he deems responsible (he also splits blame if multiple people mess up).

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Who Benefits From an Improved Trubisky Deep Ball?

| July 24th, 2019

This is part of a series of collaborations between film guru Robert Schmitz of Windy City Gridiron and stats guy Johnathan Wood of betway平台 . We’re excited to be working together to bring fans of both sites great content by combining our approaches.


Previously, we’ve identified the deep passing game as one area where Mitchell Trubisky struggled in 2018. He missed a lot of throws to open targets, which resulted both in a low completion percentage and too many interceptions.

However, we also showed that deep passing performance is highly variable, and thus appbetway必威亚洲官网 , especially with some tweaks in his throwing mechanics that can be made to help his accuracy.

Today we want to look at what targets would benefit most from that expected deep ball improvement, should it happen. In order to do that, I used Pro Football Reference’s Game Play Finder to look at what players Trubisky targeted deep most frequently in 2018. That information is shown in the table below for all five players who were primary weapons for the Bears in 2018.



Allen Robinson was Trubisky’s most frequently targeted deep threat, but Anthony Miller got – by far – the highest portion of his total targets and yards from Trubisky on deep plays. Despite finishing 5th on the team in targets and yards, both by a healthy margin, he was 3rd in deep targets and 2nd in deep yards.

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Mitch Trubisky, Do We Have a Problem? (No. Not yet.)

| June 10th, 2019

I’ve been doing a deep dive into Chicago’s offense from a variety of perspectives, and want to wrap that up today with a closer look at Trubisky. I’ve already written about him several times this offseason, talking about:

Today I want to look at how wildly his performance fluctuated with the caliber of defense that he faced. Honestly, this was not the article I set out intending to write. I first did this research with the hypothesis that Trubisky did better in early games – when there was less pressure from a national audience – and struggled in primetime games where more people were paying attention. Just watching those games, it always looked to me like Trubisky was tense, like he was putting too much pressure on himself and thus not performing well. It seemed to me like he was more relaxed in early games that got less attention, which enabled him to just go out and play.

And there might be some truth to that; Trubisky posted a passer rating of 114.4 in early games, 89.9 in late afternoon games, and 63.0 in night games. But two of the four night games (Green Bay and Seattle) came in the first two weeks of the season, when Trubisky was just not comfortable in the offense yet. He was awful in an afternoon game against Arizona the next week too before breaking out in Week 4.

I then noticed that the other two night games – when he also struggled mightily – were against the Rams and Vikings, two of the better defenses the Bears faced all season. In fact, those were statistically his 2 worst games of the year, with 3 of the next 4 bad ones being the 3 weeks before he broke out. And thus a different hypothesis emerged, and I started exploring how well Trubisky performed against good and bad defenses.

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A Complete Breakdown of the Quarterback Position’s Efficiency for 2018

| June 3rd, 2019

The offseason is the perfect time to do a deep dive into what exactly we saw on the field last year, so today I want to look more closely at how Chicago’s QBs performed in 2018. To do so, I’m going to compile all of the information about individual targets from The Quant Edge and use it to see what we can learn about QB play as a whole.

Before we begin, I want to note two limitations.

  • This doesn’t split data into individual QBs, so unfortunately I can’t separate out the games Trubisky played and use only those. Still, Trubisky accounted for 85% of Chicago’s pass attempts in 2018, so this should still be useful to help us generally learn more about him.
  • This data only includes WRs and TEs, so I will not be able to incorporate any information about the 132 pass attempts that went to RBs (and Bradley Sowell). I really wish they included Tarik Cohen in particular, considering he finished 3rd on the Bears in targets, but no such luck.

With that said, let’s get started.


Route Efficiency

How effective were Chicago’s QBs targeting various routes?

That data can be seen in the table below, sorted from most to least targeted. I also highlighted routes that were particularly efficient in green, and routes that were particularly inefficient in red.

A few thoughts:

  • The Bears loved their go routes, but they sure didn’t work well in 2018. As previously noted, Trubisky had issues with deep accuracy, and maybe that was part of the problem. And you can argue there is value in go routes to back the defense off. But still, 26% completion rate is not acceptable for a route they utilize that frequently, and there were 5 interceptions thrown on go routes as well. If you’re looking for one bright spot on go routes, Allen Robinson caught 40% of his targets for over 16 yards/target.

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